SBIR/STTR Research Award

Development of flow and vascular quantification software for the assessment of MR

Award identifier 3c77fdfd5678a5ddb6c9fa1f9cf896e5b3447f22cbce2b9ccb95d7f838b7bae1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$999,994

Program and phase

STTR · Phase II

Award year

2013

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Magnetic Resonance Innovations, Inc.
Proposal award date
Not reported
Contract end date
Not reported
UEI
NAS6FQFCRFK1
Solicitation number
PA11-097
Topic code
NHLBI

Research abstract

DESCRIPTION (provided by applicant): There has been a huge increase in demand for comprehensive quantitative analysis of neurovascular imaging data produced in the clinical setting for diseases such as multiple sclerosis, traumatic brain injury, stroke anddementia. Our objective in this project is to design and develop advanced image processing software that can rapidly and accurately analyze such data. To achieve this objective, we propose a range of novel algorithms to process data from the following MRimaging sequences widely used in the aforementioned applications: time resolved 3D contrast enhanced MR angiography (CE-MRA) for the assessment of vascular anatomy, time resolved 2D phase contrast flow imaging (PC-MRI) for the evaluation of vascular hemodynamics, susceptibility weighted imaging (SWI) for quantifying iron deposition in the brain, and fluid attenuated inversion recovery (FLAIR) imaging for the detection of white matter hyperintensities (WMH) and lesions. A variety of tools will be designed and implemented to tackle these problems including: tissue similarity mapping and active shape models to segment the vasculature in both CE-MRA and PC-MRI images; automatic tissue segmentation in the basal ganglia and thalamus for a two-region of interest analysis for iron quantification with SWI; and finally adaptive approaches incorporating fuzzy C-means, shape factor analysis, compactness and fractional anisotropy to quantify lesions and WMHs. To exploit the advantages provided by different imaging sequences, co-registration algorithms will be used to improve segmentation of vessels between CE-MRA and PC-MRI, and between 3D T1 weighted imaging and SWI. Upon finishing this project, we expect a multi-fold increase in processing efficiency and a significant increase in accuracy will be achieved. The resulting software will not only help the growth of our company, but also improve the diagnosis and treatment of neurovascular diseases. PUBLIC HEALTH RELEVANCE The huge increase in demand for a more comprehensive and accurate analysis of the vast amount of clinical MR imaging data for neurovascular diseases such as multiple sclerosis, traumatic brain injury, stroke and dementia is the driving force for th development of more advanced image processing software in our company. In this project, we propose an integrated approach to develop a set of processing software for imaging sequences that target the assessment of both anatomy and function of the neurovasculature system. The results will lead to a better access to quantitative data about the brain's vasculature, flow, hemodynamics and iron content present in neurovascular diseases. The completion of this project will not only help the growth of our company by increasing processing throughput and accuracy, but also improve the diagnosis and treatment of patients with neurovascular disease.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2012–2020). Reported award amounts total $2,628,681. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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